Senior Product Manager | Applied AI

We are growing a product-management team that runs AI-powered products and applies AI across the whole product lifecycle. As a Senior Product Manager | Applied AI , you will own the vision, strategy, roadmap and delivery of one or more products — at least one of them AI-powered — while using AI day-to-day to work faster and make sharper decisions and mentoring other Product Managers as you do.

What "Applied AI" means here. This is a product role, not an engineering role. We expect confident, practical command of AI as a product manager — using it across the lifecycle and shaping AI-powered features — not the ability to build, train or tune machine-learning models as an ML engineer or data scientist would.

Req#

• Own the vision, strategy, roadmap and end-to-end delivery of one or more products, including at least one that is AI-powered

• Define requirements and use cases for AI features, treating them as probabilistic products — scoping data and use-case fit, and setting evaluation criteria, quality bars, guardrails and human-in-the-loop review as acceptance criteria

• Identify where AI can improve the product, the customer experience, internal processes or business outcomes — and build and size the case for it

• Use AI tools productively and with discipline across discovery, research synthesis, analysis, documentation, user stories, prototyping and planning — verifying outputs before relying on them

• Prioritise features, own the backlog and manage release cycles, using AI-assisted analysis to support (not replace) your decisions

• Manage the full product lifecycle, including the added considerations of AI features — model/version changes, quality drift and human oversight

• Work closely with engineering, data, design and AI/ML teams, translating product intent into requirements they can act on and their constraints into product decisions

• Set realistic expectations with clients and stakeholders about what AI can and cannot do, and communicate benefits, limitations and risks in plain language

• Mentor Product Managers and raise the team's practical AI capability by example

• 5+ years in Product Management, having managed one or more products end-to-end, including post-launch maintenance and support

• Launched more than one product (or key capability) to market, with at least one experience delivering or materially improving an AI-powered product or feature (e.g., GenAI, ML, recommendations, search or automation)

• Solid ownership of product strategy, vision and roadmap; market analysis and product visioning — including identifying and justifying where AI adds value

• Experience owning backlogs, cross-product dependencies and release cycles, and managing product lifecycle and support models

• Familiarity with product profitability, competitive positioning and pricing — including the cost, latency and quality trade-offs that shape AI-feature economics

• Expertise across multiple (3+) business domains, able to act as a business-domain SME

• Working AI literacy — what current AI (including GenAI/LLMs) can and cannot do reliably, common patterns and typical failure modes — enough to make sound product decisions and hold credible conversations with technical teams. Deep model-building knowledge is not required

• Able to influence stakeholders up to and including VP level, and to lead all critical aspects of a product launch

• Able to lead a team of Product Owners and/or Product Managers across a product line or family, guiding them through the full lifecycle

• Raises the team's practical AI proficiency — sharing verified ways of working and coaching on requirements and evaluation criteria for AI features

• Practical, daily use of AI across research, discovery, analysis, documentation, user stories, prototyping and…